Package: betaMC 1.3.4.9000

betaMC: Monte Carlo for Regression Effect Sizes

Generates Monte Carlo confidence intervals for standardized regression coefficients (beta) and other effect sizes, including multiple correlation, semipartial correlations, improvement in R-squared, squared partial correlations, and differences in standardized regression coefficients, for models fitted by lm(). 'betaMC' combines ideas from Monte Carlo confidence intervals for the indirect effect (Pesigan and Cheung, 2024 <doi:10.3758/s13428-023-02114-4>) and the sampling covariance matrix of regression coefficients (Dudgeon, 2017 <doi:10.1007/s11336-017-9563-z>) to generate confidence intervals effect sizes in regression.

Authors:Ivan Jacob Agaloos Pesigan [aut, cre, cph]

betaMC_1.3.4.9000.tar.gz
betaMC_1.3.4.9000.zip(r-4.7-any)betaMC_1.3.4.9000.zip(r-4.6-any)betaMC_1.3.4.9000.zip(r-4.5-any)
betaMC_1.3.4.9000.tgz(r-4.6-any)betaMC_1.3.4.9000.tgz(r-4.5-any)
betaMC_1.3.4.9000.tar.gz(r-4.7-any)betaMC_1.3.4.9000.tar.gz(r-4.6-any)
betaMC_1.3.4.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
betaMC/json (API)

# Install 'betaMC' in R:
install.packages('betaMC', repos = c('https://jeksterslab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jeksterslab/betamc/issues

Pkgdown/docs site:https://jeksterslab.github.io

Datasets:
  • nas1982 - 1982 National Academy of Sciences Doctoral Programs Data

On CRAN:

Conda:

confidence-intervalsmonte-carloregression-effect-sizesstandardized-regression-coefficients

3.34 score 1 stars 22 scripts 456 downloads 8 exports 0 dependencies

Last updated from:ad33403be0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK126
source / vignettesOK174
linux-releaseOK116
macos-releaseOK114
macos-oldrelOK91
windows-develOK61
windows-releaseOK74
windows-oldrelOK81
wasm-releaseOK90

Exports:BetaMCDeltaRSqMCDiffBetaMCMCMCMIPCorMCRSqMCSCorMC

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Estimate Standardized Regression Coefficients and Generate the Corresponding Sampling Distribution Using the Monte Carlo MethodBetaMC
Estimated Parameter Method for an Object of Class 'betamc'coef.betamc
Confidence Intervals Method for an Object of Class 'betamc'confint.betamc
Estimate Improvement in R-Squared and Generate the Corresponding Sampling Distribution Using the Monte Carlo MethodDeltaRSqMC
Estimate Differences of Standardized Slopes and Generate the Corresponding Sampling Distribution Using the Monte Carlo MethodDiffBetaMC
Generate the Sampling Distribution of Regression Parameters Using the Monte Carlo MethodMC
Generate the Sampling Distribution of Regression Parameters Using the Monte Carlo Method for Data with Missing ValuesMCMI
1982 National Academy of Sciences Doctoral Programs Datanas1982
Estimate Squared Partial Correlation Coefficients and Generate the Corresponding Sampling Distribution Using the Monte Carlo MethodPCorMC
Print Method for an Object of Class 'betamc'print.betamc
Print Method for an Object of Class 'mc'print.mc
Estimate Multiple Correlation Coefficients (R-Squared and Adjusted R-Squared) and Generate the Corresponding Sampling Distribution Using the Monte Carlo MethodRSqMC
Estimate Semipartial Correlation Coefficients and Generate the Corresponding Sampling Distribution Using the Monte Carlo MethodSCorMC
Summary Method for an Object of Class 'betamc'summary.betamc
Summary Method for an Object of Class 'mc'summary.mc
Sampling Variance-Covariance Matrix Method for an Object of Class 'betamc'vcov.betamc